Analysis of different combinations of meteorological parameters in predicting the horizontal global solar radiation with ANN approach: A case study

Out of the six ANN models with all the possible combination of input variables, ANN-2 and ANN-3 have given best prediction with the combinations of [DT, Ho] and [DT, Ho, So] respectively. The statistical tool Relative Root Mean Square Error (RRMSE) showed the least value of 3.96% with [DT, Ho] inputs. The ANN-1 trained with calculated approximate sunshine hours (Sa) has also shown high prediction accuracy. Sunshine based model and temperature based model are validated with ANN-1, ANN-2 and ANN-3 architectures. Results showed that the developed ANN models outperform the considered empirical models. The combination of [So, Ho] has produced excellent estimation, which are theoretical parameters and does not require any measured meteorological parameters. Superior performance is observed with less number of inputs which are readily available for any location.